Conference Paper
Simple Random Logic Programs.
DOI: 10.1007/9783642042386_20 Conference: Logic Programming and Nonmonotonic Reasoning, 10th International Conference, LPNMR 2009, Potsdam, Germany, September 1418, 2009. Proceedings
Source: DBLP

Chapter: Simple but Hard Mixed Horn Formulas
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ABSTRACT: We study simple classes of mixed Horn formulas, in which the structure of the Horn part is drastically constrained. We show that the SAT problem for formulas in these classes remains NPcomplete, and demonstrate experimentally that formulas randomly generated from these classes are hard for the present SAT solvers, both complete and localsearch ones.07/2010: pages 382387;  [Show abstract] [Hide abstract]
ABSTRACT: This paper develops automated testing and debugging techniques for answer set solver development. We describe a flexible grammarbased blackbox ASP fuzz testing tool which is able to reveal various defects such as unsound and incomplete behavior, i.e. invalid answer sets and inability to find existing solutions, in stateoftheart answer set solver implementations. Moreover, we develop delta debugging techniques for shrinking failureinducing inputs on which solvers exhibit defective behavior. In particular, we develop a delta debugging algorithm in the context of answer set solving, and evaluate two different elimination strategies for the algorithm. Comment: 18 pagesTheory and Practice of Logic Programming 07/2010; · 0.29 Impact Factor 
Article: Random Logic Programs: Linear Model
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ABSTRACT: This paper proposes a model, the linear model, for randomly generating logic programs with low density of rules and investigates statistical properties of such random logic programs. It is mathematically shown that the average number of answer sets for a random program converges to a constant when the number of atoms approaches infinity. Several experimental results are also reported, which justify the suitability of the linear model. It is also experimentally shown that, under this model, the size distribution of answer sets for random programs tends to a normal distribution when the number of atoms is sufficiently large.Theory and Practice of Logic Programming 06/2014; · 0.90 Impact Factor
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